Remote Sensing

Code:

EGEO3003

Acronym:

EGEO3003

Level:

300

Keywords
Classification	Keyword
OFICIAL	Surveying Engineering

Instance: 2018/2019 - 1S

Active?	Yes
Responsible unit:	Department of Geosciences, Environment and Spatial Plannings
Course/CS Responsible:	Bachelor in Chemistry

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:B	0	Official Study Plan	3	-	6	56	162
L:CC	0	Plano de estudos a partir de 2014	2	-	6	56	162
			3
L:F	0	Official Study Plan	2	-	6	56	162
			3
L:G	0	study plan from 2017/18	3	-	6	56	162
L:M	0	Official Study Plan	2	-	6	56	162
			3
L:Q	0	study plan from 2016/17	3	-	6	56	162

Teaching language

Suitable for English-speaking students

Objectives

This course presents the general concepts, techniques and applications of satellite remot sensing. There is a strong component in earth observation and ocean applications. The students learn these concepts and techniques by writting computer code (in MATLAB language) for digital image processing of satellite data and their applications.

Learning outcomes and competences

At the end of the semester the students should have learned some essential techniques of satellite remote sensing and digital image processing. The students should have learned the basis of remote sensing and be prepared to apply the techniques to new and futures satellite sensors in earth observation. The student should be able to plan and implement remote sensing algorithms to extract geophysical information from satellite imagery using appropriate sofware.

Working method

Presencial

Program

1. Introduction to remote sensing and associated scientific applications. 2. Basic concepts of digital image processing. 3. Electromagnetic radiation. 4. Earth observing satellites and other platforms used for remote sensing of the earth. 5. Remote sensing in the visible wavebands and ocean color concepts. 6. Thermal infrared and sea surface temperature (SST). 7. Introduction to weather radars (non-doppler systems). 8. Doppler radars in weather radar systems. 9. Synthetic Apertur Radars (SAR), radar altimeter and marine applictions. 

Mandatory literature

Ian S. Robinson; Discovering the Ocean from Space (The unique applications of satellite oceanography), 2010. ISBN: 978-3-540-24430-1
Chris Jackson & John Apel; Synthetic Aperture Radar Marine Users Manual, U.S. Department of Commerce, 2004. ISBN: 0-16-073214-X

Complementary Bibliography

Martin Seelye; An introduction to ocean remote sensing. ISBN: 0-521-80280-6
Richards, J.A., Jia, X.; Remote Sensing Digital Image Analysis - An Introduction, Springer-Verlag, 2000
Gonzalez, R.C., Woods, R.E.; Digital Image Processing, Addison-Wesley, 2008

Teaching methods and learning activities

Lessons about theoretical concepts are presented as power point oral presentations. Practical lectures in front of a computer with a strong programming component. A programming Project is proosed every week and must be solved during that week. The programming language is MATLAB, and the students learn the applications and essentials of digital image processing. 

Software

MATLAB

keywords

Natural sciences > Environmental science > Global change > Climate change
Technological sciences > Technology > Marine technology > Remote sensing: satelliteborne sensors, airborne
Technological sciences > Technology > Remote sensing

Evaluation Type

Distributed evaluation without final exam

Assessment Components

designation	Weight (%)
Participação presencial	0,00
Teste	50,00
Trabalho laboratorial	50,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Trabalho laboratorial	9,00
Total:	9,00

Eligibility for exams

The students must submit at least three computer code assignments to solve proposed projects in remote sensing applications and using digital image processing techniques. In addition there is a written test at the end of the semester to evaluate theoretical concepts about remote sensing techniques. 
A course project may be proposed to be handed in by the end of the semester.

Calculation formula of final grade

Evaluation requires two components: 1) Weekly computer programming in MATLAB (1/2); 2) Written test at the end of semester (1/2); 

Examinations or Special Assignments

NA

Internship work/project

NA

Special assessment (TE, DA, ...)

Written test + computer course projet in MATLAB.

Classification improvement

By taking an exame.